Mobility data processing apparatus, mobility data processing method and mobility data processing system

ABSTRACT

A management server is adapted to be provided with: a field data managing unit configured to store mobility data of mobility instances; a group possibility degree determining unit configured to execute a predetermined process for improving identification of mobility context, for the mobility data; and a group extracting unit configured to, based on a time distance and a spatial distance between mobility data of one mobility instance and mobility data of another mobility instance, identify mobility context of the one mobility instance after the process is performed.

CROSS-REFERENCE TO PRIOR APPLICATION

This application relates to and claims the benefit of priority fromJapanese Patent Application No. 2017-057232 filed on Mar. 23, 2017, theentire disclosure of which is incorporated herein by reference.

BACKGROUND

The present invention relates to a mobility data processing apparatusand the like for analyzing mobility data about a mobility instance (amobile body).

Recently, the term IoT (Internet of Things) has been attractingattention. IoT is variously interpreted. In the present specification,it is assumed that IoT means to, by sensing and collecting data aboutactivity statuses of various objects and things in the real world, andanalyzing and utilizing the data, create new value.

As a use case of such IoT, guidance for reducing congestion can begiven. Specifically, if congestion of persons (pedestrians) at afacility such as a station or congestion such as a traffic jam on a roadoccurs, the congestion is reduced by appropriately guiding mobile bodies(referred to as mobility instances) such as persons and cars to a vacantfacility or road. For this purpose, by sensing, collecting and analyzingthe congestion status of the congested area and the availability statusof a guidance destination, and, sometimes, by analyzing profileinformation such as the tastes of the individual person together, anappropriate guidance destination is identified, and guidance isperformed by sending a notification to terminal such as smartphone andmobile phone owned by the person or terminal such as on-board device ofthe car so that congestion is reduced.

As for measurement of the congestion status, there may be a case wherethe congestion status is directly measured with a camera or the like, orthere may be a case where pieces of position data (referred to asmobility data) acquired by the mobile terminals of the individualpersons or GPS's which are the on-board devices of the cars areaggregately totalized to make a judgment. As for the notification toperform the guidance, it is also conceivable to, in addition toprovision of information, give an incentive, for example, bydistributing a coupon for a movement destination facility in some casesso that motivation for the guidance is improved.

As another use case of IoT, digital signage for improving supply-demandefficiency is given. Specifically, an advertisement is presented toperson at an appropriate place and an appropriate timing. The person maybe pedestrian or that in a facility. Driver and passenger of passengercar or passenger of other transportation means is also conceivable. Thedelivery destination may be personal mobile terminal or may be a displayin a facility. In order to realize this use case, by performing analysisbased on position information (which can be measured, for example, byGPS's of mobile terminals), profile information and the like about thepersons, and, sometimes, by analyzing the surrounding situation (forexample, the stock status of particular sales products in a retail storeor the seat availability status of an eating house) and the like also,delivery content is decided. Then, the advertisement is delivered, inconsideration of positional matching with proper neighboring displaysalso in the case of display delivery.

In the various use cases described above, it is thought that the effectcan be improved by targeting not each individual person but each group.This is because a person acts not only as an individual but also ingroups based on social relationships such as a family relationship, aworkplace relationship and a friend relationship, and, furthermore, actsin groups based on differently configured social relationships accordingto times, places and scenes.

For example, in a use case where resolution of congestion is realizedwhen persons are moving as a group based on a social relationship, ifguidance is performed for each individual person, there is a possibilitythat the capacity of a guidance destination is not enough to accommodatethe group or that the guidance destination does not meet the tastes ofthe group. Therefore, by performing guidance in consideration of asituation of the group, improvement of the effect of congestionresolution is expected. Further, in a use case of digital signage,advertisement delivery corresponding to characteristics of group becomespossible, and improvement of cost-effectiveness is expected.

For example, Japanese Patent Laid-Open No. 2013-13143 discloses atechnique of grouping mobile phone terminals based on information suchas space, time and speed about the individual mobile phone terminals.

SUMMARY

For example, the technique of Japanese Patent Laid-Open No. 2013-13143can identify a statistical population group by region but cannotidentify a group based on a social relationship. For example, groupsbased on different social relationships move by the same publictransportation means, it is not possible to distinguish the groups asseparate groups by position, time and speed information.

In general, since mobile terminals used to measure mobility data aboutpersons are carried by the individual persons, it is difficult tosuccessively identify a group based on a social relationship theconfiguration of which dynamically changes, from the mobility datameasured by the individual mobile terminals.

Thus, it is difficult to identify context about movement of a mobilityinstance, such as whether the mobility instance moves belonging to agroup based on the same social relationship as another mobility instanceor moves belonging to a different group.

The present invention has been made in view of the above situation, andan object is to provide a technique capable of appropriately identifyingmobility context which is information indicating, for a mobilityinstance, a characteristic of a movement relationship with anothermobility instance.

In order to achieve the above object, a mobility data processingapparatus according to one aspect is a mobility data processingapparatus identifying, for one or more movable mobility instancesexisting in real space, mobility context which is information indicatinga characteristic of a movement relationship with another mobilityinstance, the apparatus including: a mobility data managing unitconfigured to store pieces of mobility data including space informationand time information about the plurality of mobility instances; aprocess executing unit configured to execute a predetermined process forimproving identification of the mobility context, for the pieces ofmobility data; and a mobility context identifying unit configured to,based on a time distance and a spatial distance between a piece ofmobility data of one mobility instance and a piece of mobility data ofanother mobility instance, identify mobility context of the one mobilityinstance after the process by the process executing unit.

According to the present invention, it is possible to appropriatelyidentify mobility context which is information indicating, for amobility instance, a characteristic of a movement relationship withanother mobility instance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an entire configuration diagram of a mobility data processingsystem according to an embodiment;

FIG. 2 is a diagram showing a configuration example of an update targetmanagement table according to the embodiment;

FIG. 3 is a diagram showing configuration examples of a part of tablesmanaged by a field data managing unit according to the embodiment;

FIG. 4 is a diagram showing configuration examples of the remainingtables managed by the field data managing unit according to theembodiment;

FIG. 5 is a diagram showing a configuration example of a grouppossibility degree temporary management table according to theembodiment;

FIG. 6 is a diagram showing configuration examples of tables managed bya common data management unit according to the embodiment;

FIG. 7 is a sequence chart showing an operation example of a mobilitydata use system according to the embodiment;

FIG. 8 is a flowchart showing an example of a process by a field dataacceptance processing unit according to the embodiment;

FIG. 9 is a flowchart showing an example of a process by an instancedata processing unit according to the embodiment;

FIG. 10 is a flowchart showing an example of a process by a group dataprocessing unit according to the embodiment;

FIG. 11 is a flowchart showing an example of a process by a groupextracting unit according to the embodiment;

FIG. 12 is a flowchart showing an example of a process by a notificationcontent processing unit according to the embodiment;

FIG. 13 is a diagram showing an example of a GUI of a terminal of a useraccording to the embodiment; and

FIG. 14 is a hardware configuration diagram of a management server 101according to the embodiment.

DETAILED DESCRIPTION OF THE EMBODIMENT

An embodiment will be described with reference to drawings. Theembodiment described below does not limit the invention according to theclaims. Further, all of various components and combinations thereofdescribed in the embodiment are not necessarily essential for solutionmeans of the invention.

In the description below, a mobility instance is a general term forthings (mobile bodies) moving on a field (real space). The mobileinstance includes a person, a car such as a passenger car, a bus and atruck (and its driver and a passenger) and a public transportation bodysuch as a bus and a railway car.

Further, a mobility group is a term referring to a group which isconstituted by one or more mobility instances, and the one or moremobility instances of which have a strong social relationship and arethought to move as one at the time of movement.

Further, mobility data includes position information about a mobilityinstance and time point information about time point when the positioninformation was measured. Further, the mobility data may includeinformation such as speed information and movement state in addition tothe position information and the time point information. The mobilitydata may be measured by a terminal carried by (or mounted on) a mobilityinstance or may be measured by a system monitoring movement of mobilityinstances (for example, a railway operation monitoring system) or thelike.

Further, a capacity instance is a general term for things (accommodationbodies) for accommodating mobility instances on a field. The capacityinstance includes, for example, a public infrastructure such as a roadand a station facility, and a commercial facility such as an eatinghouse. Further, the capacity instance is not necessarily independentfrom a mobility instance. For example, a transportation body like a busis both of a capacity instance and a mobility instance. Capacityinstances may be distinguished, for example, by referring to a thingwhich socially influences much at the time of congestion, like a publicinfrastructure as an infra capacity instance and referring to a thingwhich brings about improvement of profit by performing accommodation,like an eating house as a provider capacity instance. Here, the infracapacity instance is a capacity instance from which mobility instancesare to be guided to another place at the time of congestion, and theprovider capacity is a capacity instance to be a guidance destinationfor the mobility instances at the time of congestion of the infracapacity instance.

Further, mobility context of a mobility instance is informationindicating a characteristic of a movement relationship of the mobilityinstance with another mobility instance. As the mobility context, forexample, information showing that there is a strong possibility that amobility instance is moving with another mobility instance as being inthe same group, information showing that there is a strong possibilitythat the mobility instance is not moving as being in the same group, andthe like are included.

Further, though time point information is shown, for example, in asimplified form of “time: minute: second” in the present specificationand drawings, for example, a form in which information such as year,month and day is also included is also possible. Further, time pointinformation may be in a form in accordance with formats such as an ISOstandard form and a UNIX® time stamp.

Further, though position information is in a (x, y) coordinate form inthe present specification and drawings for example, the positioninformation may be in a form of latitude and longitude. Further, a formin which height (altitude) information is included is also possible.Further, the position information may be information by an addressexpression, and an address expression and a coordinate expression may bemixed. In the case of causing a coordinate expression and an addressexpression to be mixed, the expressions can be mutually converted usinga well-known technique such as geocoding and used.

FIG. 1 is an entire configuration diagram of a mobility data processingsystem according to the embodiment.

A mobility data processing system 100 includes a management server 101as an example of a mobility data processing apparatus, terminals 102 aof users 102, and a gateway 106. The management server 101 receivesmobility data about mobility instances 104 and data about capacityinstances 105 existing in a field (real space) 103 via a communicationnetwork not shown (for example, the Internet, a mobile communicationnetwork or the like) and the gateway 106 and executes various processes.The gateway 106 performs format conversion or load balancing of variousdata transmitted via the communication network. The terminal 102 a ofthe user 102 communicates with the management server 101 via thecommunication network and display various information.

In the field 103, the mobility instances 104 and the capacity instances105 exist. For example, if a mobility instance 104 is a person, mobilitydata about the mobility instance 104 is transmitted from a terminal 104a owned by the person to the management server 101; if the mobilityinstance 104 is a car, the mobility data is transmitted from a terminal(an on-board device) 104 b mounted on the car to the management server101; and, if the mobility instance 104 is a instance like a train ofwhich movement is monitored by a monitoring system, the mobility data istransmitted from the monitoring system to the management server 101. Theperson who is the mobility instance 104 and the terminal 104 a owned bythe person may correspond to a user 102 and a user terminal 102 a.

The management server 101 includes a field request accepting unit 111, afield data acceptance processing unit 112, a field data managing unit113, a common data managing unit 114, an instance data processing unit115, a group data processing unit 116, a notification content processingunit 117, a user process executing unit 118 and a user request acceptingunit 119. The management server 101 is coupled to a console 120 operatedby an administrator who manages the management server 101.

The field request accepting unit 111 executes a process for accepting arequest generated from the field 103 side. Requests generated from thefield 103 (specifically, various terminals and the like in the field103) includes reception of data from the field 103.

The field data acceptance processing unit 112 processes data received bythe field request accepting unit 111. The field data acceptanceprocessing unit 112 includes a data identifying unit 121, a stateupdating unit 122 and an update target management table 123. Eachcomponent of the field data acceptance processing unit 112 will bedescribed later with reference to FIGS. 2 and 8.

The field data managing unit 113 is an example of a mobility datamanaging unit and manages data generated from the field 103. The fielddata managing unit 113 includes a mobility data management table 131, aprovider capacity state management table 132, a mobility eventmanagement table 133, a mobility instance state management table 134, amobility group management table 135 and an infra capacity statemanagement table 136. Each component of the field data managing unit 113will be described later with reference to FIGS. 3 and 4.

The common data managing unit 114 manages reference data to be used fora process for weighting mobility data and the like. The common datamanaging unit 114 includes a filtering data management table 161, afiltering process management table 162 and a profile management table163. Each component of the common data managing unit 114 will bedescribed later with reference to FIG. 6.

The instance data processing unit 115 processes data for each mobilityinstance. The instance data processing unit 115 includes an eventextracting unit 141 as an example of an extraction unit and an eventaggregating unit 142 as an example of an aggregation unit. Eachcomponent of the instance data processing unit 115 will be describedlater with reference to FIG. 9.

The group data processing unit 116 is an example of a process executingunit and performs a process for identifying a group of mobilityinstances. The group data processing unit 116 includes a grouppossibility degree determining unit 151, a group extracting unit 152 asan example of a mobility context identifying unit and a groupidentifying unit, and a group possibility degree temporary managementtable 153. Each component of the group data processing unit 116 will bedescribed later with reference to FIGS. 5 and 10.

The notification content processing unit 117 performs a process fordetermining necessity/unnecessity of a notification process andnotification content. The notification content processing unit 117includes a notification necessity/unnecessity determining unit 171 as anexample of an excess detecting unit, and a notification contentdetermining unit 172. Each component of the notification contentprocessing unit 117 will be described later with reference to FIG. 12.

The user process executing unit 118 performs delivery and notificationof data to the users 102 (strictly, the user terminals 102 a) andperforms processes such as performing data search based on searchrequests from the users 102 (strictly, the user terminals 102 a). Theuser process executing unit 118 includes a data delivering unit 181, adata notifying unit 182 and a data searching unit 183.

When activated by the user request accepting unit 119, the datasearching unit 183 searches for various information based on a searchrequest from a user terminal 102 a. For example, if accepting a searchrequest for searching for the capacity state of a provider capacityinstance, the data searching unit 183 performs a search process for theprovider capacity state management table 132 based on a space range(ranges of X and Y) and a time range (from the present to a certain timepoint in the past) targeted by search of the search request, typeinformation and the like. Further, if accepting a search request forsearching for congestion information about various infra capacities,such as a traffic jam and facility congestion, the data searching unit183 performs a search process using the infra capacity state managementtable 136. Further, if accepting a search request for searching for aposition of a particular type of mobility instance such as a position ofa bus or a train, the data searching unit 183 performs a search processusing the mobility instance state management table 134. Further, ifaccepting a search request for searching for a movement record(trajectory data) in the past, the data searching unit 183 performs asearch process using the mobility data management table 131. Further, ifaccepting a search request for searching for an event record in thepast, the data searching unit 183 performs a search process using themobility event management table 133. As for such a search, an accesscontrol process for preventing privacy data from being searched isnecessary. For example, a list permitting search only about particularinstance IDs (a white list) may be prepared so that search is performedaccording to the list.

The data delivering unit 181 transmits various pieces of information tothe user terminal 102 a. For example, the data delivering unit 181transmits notification content decided by the notification contentdetermining unit 172 to terminals 102 a of mobility instances (users)belonging to the same mobility group. Further, the data delivering unit181 transmits a result of a search process by the data searching unit183 to the terminal 102 a of a search request source user.

The user request accepting unit 119 performs a process for callingvarious processes of the user process executing unit 118 based on aprocess request from a user 102 (a terminal 102 a). For example, ifreceiving a search request from a terminal 102 a, the user requestaccepting unit 119 activates the data searching unit 183.

The console 120 is an interface for the administrator of the managementserver 101 to make various configurations for the management server 101and the like.

FIG. 14 is a hardware configuration diagram of the management server 101according to the embodiment.

The management server 101 is, for example, a general computer andincludes a CPU (Central Processing Unit) 1401, a memory 1402, anauxiliary storage device 1403, a communication interface 1404, a mediainterface 1405 and an input/output device 1406.

The communication interface 1404 is an interface for communicating withother apparatuses (terminals 102 a, 104 a, 104 b and the like) via anetwork 1408. The CPU 1401 executes a program stored in the memory 1402or the auxiliary storage device 1403 and executes various processesusing data stored in the memory 1402 or the auxiliary storage device1403. The memory 1402 is, for example, a RAM (Random Access Memory) andstores the program executed by the CPU 1401, data and the like. Theauxiliary storage device 1403 is, for example, a hard disk, a flashmemory, a RAM or the like and stores the program executed by the CPU1401 and data used by the CPU 1401.

An external storage medium 1407 is attachable to and detachable from themedia interface 1405, and the media interface 1405 mediates input/outputof data to/from the external storage medium 1407. The console 120operated by the administrator of the management server 101 is coupled tothe input/output device 1406, and the input/output device 1406 performsinput/output of information to/from the console 120.

As shown in FIG. 1, each functional unit implemented in the managementserver 101 is configured by the CPU 1401 executing the program stored inthe auxiliary storage device 1403 or the memory 1402. Further,information managed by each functional unit (for example, varioustables) is stored in the memory 1402 or the auxiliary storage device1403.

The program executed by the CPU 1401 may be acquired from anotherapparatus via the communication interface 1404 as necessary or may beacquired by reading the program from an available medium via the mediainterface 1405. The medium is, for example, a communication medium (thatis, a wired, wireless or optical network, or a carrier or a digitalsignal propagated through the network) or the external storage medium1407 attachable to and detachable from the media interface 1405.

Next, a configuration of the update target management table 123 of thefield data acceptance processing unit 112 will be described.

FIG. 2 is a diagram showing a configuration example of an update targetmanagement table according to the embodiment.

The update target management table 123 is a table specifying a table tobe updated when the management server 101 receives data from the field103. The update target management table 123 stores, for each instancetype, an entry having fields of an instance type 201 and an updatetarget table 202. In the instance type 201, an instance type is stored.In the update target table 202, the name of a table to be updated whendata of an instance type stored in the instance type 201 of the entry isreceived is stored.

For example, according to the top entry in FIG. 2, it is seen that, ifthe instance type is “person”, the mobility data management table 131and the mobility instance state management table 134 are to be updated.

Next, configurations of tables managed by the field data managing unit113 will be described.

FIG. 3 is a diagram showing configuration examples of a part of tablesmanaged by a field data managing unit according to the embodiment, andFIG. 4 is a diagram showing configuration examples of the remainingtables managed by the field data managing unit according to theembodiment.

As shown in FIGS. 3 and 4, the field data managing unit 113 manages themobility data management table 131, the provider capacity statemanagement table 132, the mobility event management table 133, themobility instance state management table 134, the mobility groupmanagement table 135 and the infra capacity state management table 136.A capacity instance managing unit is configured with the providercapacity state management table 132 and the infra capacity statemanagement table 136.

The mobility data management table 131 manages mobility data transmittedfrom the mobility instances 104 (or the terminal 104 a and the likerelated to the mobility instances 104). The mobility data managementtable 131 stores mobility data of the mobility instances 104 from thepast to the present and can be said to manage a movement history (amovement trajectory) about each mobility instance 104.

The mobility data management table 131 stores, for each piece oftransmitted mobility data, an entry including fields of a mobilityinstance ID 301, a mobility instance type 302, a time point 303 and aposition 304. In the mobility instance ID 301, an identifier foruniquely identifying a mobility instance 104 on the field 103 is stored.In the mobility instance type 302, a category name indicating a mobilityinstance type such as “person” and “car” is stored. In the time point303, time point at which the mobility data was generated is stored. Inthe position 304, position information (for example, a measurement valueby a GPS or the like) indicating a geographical position at which themobility instance 104 existed when the mobility data was generated isstored.

The provider capacity state management table 132 is a table whichmanages the present and past states of provider capacity instances amongthe capacity instances 105. The provider capacity state management table132 stores, for each provider capacity instance, an entry having fieldsof a provider capacity instance ID 331, a capacity instance type 332, anaccommodation target mobility instance type 333, a position 334 and acapacity state 335.

In the provider capacity instance ID 331, an identifier for uniquelyidentifying the provider capacity instance on the field 103 is stored.In the capacity instance type 332, a category name indicating a capacityinstance type such as “eating house” and “accommodation facility” isstored. In the accommodation target mobility instance type 333, acategory name indicating a mobility instance type which the capacityinstance corresponding to the entry can be accommodated is stored. Inthe position 334, position information about the capacity instance isstored. In the capacity state 335, vacant state information about thecapacity instance is stored.

The mobility event management table 133 manages events which occur inrelation to the mobility instances 104. Here, as the events, forexample, speed reduction of a car, a person getting out of the car andthe like are given. Such an event can be used to estimate the congestionstatus of an infra capacity instance such as a road. This is because,while a traffic volume can be measured, for example, by counting thenumber of mobility instances on a road, a traffic jam status is notnecessarily reflected, but, on the other hand, it can be thought that anevent such as speed reduction reflects a traffic jam status.

The mobility event management table 133 stores, for each occurred event,an entry including fields of an event ID 351, a time point 352, aposition 353, a mobility instance ID 354 and an event type 355. In theevent ID 351, an identifier for uniquely identifying the event isstored. In the time point 352, time point at which the event of theentry occurred is stored. In the position 353, information about aposition at which the event of the entry occurred is stored. In themobility instance ID 354, an ID of a mobility instance to which theevent of the entry is related is stored. In the event type 355, acategory name indicating the type of the event of the entry is stored.Afield for storing related parameters (such as car speed) of the eventmay be provided for this entry.

The mobility instance state management table 134 manages the present andpast states of the mobility instances 104. The mobility instance statemanagement table 134 stores, for each mobility instance 104, an entryincluding fields of a mobility instance ID 401, a mobility instance type402, a position 403, a mobility instance state 404 and a final updatetime 405.

In the mobility instance ID 401, an identifier for uniquely identifyingthe mobility instance 104 on the field 103 is stored. In the mobilityinstance type 402, a category name indicating the type of the mobilityinstance 104 is stored. In the position 403, position information aboutthe mobility instance 104 is stored. In the mobility instance state 404,a category name indicating the state of the mobility instance 104 isstored. In the final update time 405, final update time point at whichthe state of the mobility instance 104 of the entry was updated isstored. Each entry may be further provided with a field for storing moredetailed information (for example, speed) about a category name in themobility instance state 404.

The mobility group management table 135 manages pieces of informationabout group (mobility group) for movement of the mobility instance 104.The mobility group management table 135 stores, for each mobilityinstance 104, an entry including fields of a mobility instance ID 421, amobility instance type 422, a mobility group ID 423 and an update time424. In the mobility instance ID 421, an identifier for uniquelyidentifying the mobility instance 104 is stored. In the mobilityinstance type 422, a category name indicating the type of the mobilityinstance 104 is stored. In the mobility group ID 423, an identifier foruniquely identifying a group to which the mobility instance 104 belongsis stored. In the update time 424, time point at which group informationwas identified is stored.

The infra capacity state management table 136 manages the present andpast capacity states of infra capacities. The infra capacity statemanagement table 136 stores, for each infra capacity instance, an entryincluding fields of an infra capacity ID 441, an infra capacity type442, a position 443, a capacity state 444 and a time point 445. In theinfra capacity ID 441, an identifier for uniquely identifying the infracapacity instance is stored. In the infra capacity type 442, a categoryname indicating the type of the infra capacity instance is stored. Inthe position 443, position information about the infra capacity instanceis stored. In the capacity state 444, the state of the infra capacityinstance, for example, a congestion degree is stored. In the time 445,time point at which infra capacity state information was updated isstored. Since there are some infra capacity instances that cannot beexpressed by coordinates of one point such as a road, a field forperforming management with an expression such as a row of dots and anarea may be added.

In the present embodiment, by making an abstract table configurationabsorbing differences among types, like the various tables of the fielddata managing unit 113, instead of creating a table for each type ofmobility instances and capacity instances, it is possible to compatiblewith various types of instances.

Next, a configuration of the group possibility degree temporarymanagement table 153 of the group data processing unit 116 will bedescribed.

FIG. 5 is a diagram showing a configuration example of a grouppossibility degree temporary management table according to theembodiment.

The group possibility degree temporary management table 153 is a tablewhich manages weight information for mobility data as the degree ofgroup possibility, which is to be used for determining a group ofmobility instances 104. The group possibility degree temporarymanagement table 153 stores an entry including fields of a mobilityinstance ID 501, a mobility instance type 502, a time point 503, aposition 504 and a group possibility degree 505. In the mobilityinstance ID 501, an identifier for uniquely identifying the mobilityinstance 104 is stored. In the mobility instance type 502, a categoryname indicating the type of the mobility instance 104 is stored. In thetime point 503, time point at which the mobility data was acquired isstored. In the position 504, information about a position at which themobility data was generated is stored. In the group possibility degree505, weight information at the time of identifying a group for themobility data is stored. In the present embodiment, the weight is avalue in a range between 0 and 1 including 0 and 1, and shows that, asthe value is closer to 1, the degree of easiness at the time ofidentifying a group is higher.

Next, configurations of tables managed by the common data managing unit114 will be described.

FIG. 6 is a diagram showing configuration examples of tables managed bya common data management unit according to the embodiment.

As described before, the common data managing unit 114 includes thefiltering data management table 161, the filtering process managementtable 162 and the profile management table 163.

The filtering data management table 161 is a table which managesreference data for performing a mobility data weighting process. Thefiltering data management table 161 stores, for each piece of data usedfor filtering, an entry including fields of a filtering data type 601and a data storage destination 602. In the filtering data type 601, acategory name indicating the type of reference data to be used to weightmobility data is stored. In the data storage destination 602, a storagedestination or acquisition method for the filtering data of the entry isstored. In the example of FIG. 6, an entry 611 shows that, as thefiltering data, map data (expressed by a graph structure or the like) isstored as a file Road.xml in the XML (eXtensible Markup Language)format, and an entry 612 shows that bus probe data (mobility data of abus) can be acquired from the mobility data management table 131.

The filtering process management table 162 is a table which managesprocess content of the weighting process. The filtering processmanagement table 162 stores, for each piece of data used for filtering,an entry including fields of a filtering data type 621 and a filteringprocessing method 622. In the filtering data type 621, a category nameindicating the type of reference data to be used to weight mobility datais stored. In the filtering processing method 622, a method for aprocess for giving weight to the mobility data using the reference dataof the filtering data is stored. In the example of FIG. 6, an entry 633shows that a process for map matching with map data is performed formobility data so that such mobility data that is determined to showbeing on a railway track is removed (in the present embodiment, weightto be given to the mobility data is set to 0); and an entry 634 showsthat a spatiotemporal distance (a distance based on time information andspace information) from bus probe data is calculated for mobility dataso that such mobility data that the distance is within a predeterminedrange is removed (in the present embodiment, weight is set to 0). Thoughthe weight to be given to mobility data is set to 0 in the example ofFIG. 6, the weight to be given may be a value within a range between 0and 1 including 0 and 1.

Here, the weight to be given to mobility data will be described. Thisweight is weight regarding easiness of identification of mobilitycontext (for example, information distinguishing whether or not amobility instance belongs to the same group (a mobility group) withregard to movement) for mobility data. In the present embodiment, theweight regarding easiness of identification is increased ifidentification of the mobility context is easy, and the weight isdecreased if identification is difficult. For example, as data fromwhich it is difficult whether or not a mobility instance belongs to thesame group with regard to movement, mobility data measured at a highlypublic place where a plurality of different groups are easily mixed,such as inside a railway car, a bus and a station facility, is given. Onthe other hand, as data from which it is easy to distinguish whether ornot a mobility instance belongs to the same group with regard tomovement, mobility data measured at a place where different groups areeasily independent from one another, for example, mobility data on ageneral road where the groups are walking or moving in cars is given.

The profile management table 163 manages supplementary information fordeciding appropriate guidance destinations for the mobility instance104, for example, profile information about the tastes of the mobilityinstance 104. The profile management table 163 stores, for each mobilityinstance 104, an entry including fields of a mobility instance ID 641and a profile 642. In the mobility instance ID 641, an identifier foruniquely identifying the mobility instance 104 is stored. In the profile624, profile information such as the tastes of the mobility instance 104is stored. As the profile information, for example, the type of acapacity instance which allows being notified as a guidance destinationis given.

Next, a process operation of the mobility data use system 100 will bedescribed.

FIG. 7 is a sequence chart showing an operation example of a mobilitydata use system according to the embodiment.

The mobility instance 104 (or the terminal 104 a or the like carried bythe mobility instance 104) transmits mobility data to the managementserver 101 at appropriate timings (steps a1 to a3). Further, thecapacity instance 105 (or terminal provided for the capacity instance105) transmits capacity state data about the capacity instance 105 tothe management server 101 at appropriate timings (steps a1 to a3). Themobility instance 104 and the capacity instance 105 transmit the datavia a communication network or the gateway 106 though it is not shown.

In the management server 101, the field data acceptance processing unit112 and the instance data processing unit 115 perform processes for thereceived data (steps a4 to a6). Specifically, the field data acceptanceprocessing unit 112 and the instance data processing unit 115 add datato or update data in the field data managing unit 113 according to theclassification of the received data. Further, the field data acceptanceprocessing unit 112 and the instance data processing unit 115 alsoperform processes such as for event extraction and aggregation of infracapacity states as necessary. The processes may be executed atappropriate timings. The processes may be executed with a timing ofreceiving the data as a trigger, or may be periodically executed bybuffering the received data.

The group data processing unit 116 of the management server 101 performsa process for identifying groups of the mobility instances 104 from data(mobility data about the mobility instances 104) accumulated in thefield data managing unit 113, and adds a result of the process to thefield data managing unit 113 or updates the data in the field datamanaging unit 113 with the result (step a7). This process can beperformed at an appropriate timing and is not necessarily required to besynchronized with receiving of data.

Further, the notification content processing unit 117 and the userprocess executing unit 118 of the management server 101 decide whetheror not to make a notification to the terminal 102 a of the user 102 andnotification content based on group information and various pieces ofcapacity state information accumulated in the field data managing unit113, and perform a process for notification to the terminal 102 a of theuser 102 as necessary (step a8). This process can be performed at anappropriate timing and is not necessarily required to be synchronizedwith receiving of data or a timing of updating content of the data inthe field data managing unit 113.

The user terminal 102 a of the user 102 displays the notificationcontent received from the user process executing unit 118 on screen(step a9).

Next, a process operation of the field data acceptance processing unit112 of the management server 101 will be described.

FIG. 8 is a flowchart showing an example of a process by a field dataacceptance processing unit according to the embodiment.

The field data acceptance processing unit 112 receives data from aninstance (a mobility instance 104 or a capacity instance 105) on thefield 103 and updates an appropriate table in the field data managingunit 113 (S801 to S803).

Specifically, the field data acceptance processing unit 112 receivesdata from an instance (a mobility instance or a capacity instance) onthe field 103 (S801). Data received from a mobility instance 104includes a position, time point, a mobility instance type and the like(and speed and the like as necessary) according to the tableconfiguration of the mobility data management table 131. Data receivedfrom a capacity instance 105 includes a position, time point, a capacitystate and the like according to the table configurations of the providercapacity state management table 132 and the infra capacity statemanagement table 136.

Next, the data identifying unit 121 identifies classificationinformation (a mobility instance type or a capacity instance type) aboutthe received data (S802).

Next, the state updating unit 122 updates a related table in the fielddata managing unit 113 based on the classification information about thereceived data and information in the update target management table 123(S803). For example, if the type of the received data is mobilityinstance related (“person”, “car” or the like), the state updating unit122 adds the data to the mobility data management table 131. On theother hand, if the type of the received data is capacity instancerelated, the state updating unit 122 updates the provider capacity statemanagement table 132.

If it is possible to directly measure capacity information about aninfra capacity instance 105 and acquire the data, the state updatingunit 122 directly updates capacity information of the infra capacitystate management table 136. In this case, the instance data processingunit 115 is required not to perform an event aggregation process to bedescribed later for this infra capacity instance 105.

Further, if speed information or the like is directly included in thedata received from a mobility instance 104, the state updating unit 122may directly update data of the mobility instance state management table134. In this case, the instance data processing unit 115 is required notto perform processes such as event extraction to be described later forthis mobility instance 104.

Next, a process operation of the instance data processing unit 115 ofthe management server 101 will be described.

FIG. 9 is a flowchart showing an example of a process by an instancedata processing unit according to the embodiment.

For data acquired from the field 103, the instance data processing unit115 extracts events of mobility instances from mobility data of themobility instances to identify state information about the mobilityinstances, and to aggregate infra capacity states (S901 to S905).

First, the event extracting unit 141 performs a process for extractingevent information about each of the mobility instances (S901 and S902).

Specifically, the event extracting unit 141 performs the process ofsteps S901 and S902 described below for each mobility instance as aprocess target. In description of FIG. 9, the mobility instance as aprocess target will be referred to as a target mobility instance.

As for the target mobility instance, the event extracting unit 141compares past mobility information in the mobility data management table131 and present information in the mobility instance state managementtable 134 to extract an event (S901). Specifically, the event extractingunit 141 compares the past mobility data and present state of the targetmobility instance, and, if there is no change in the position for apredetermined time or more, regards it as a stagnation event. If thereis a predetermined amount of change or more in the position during astagnation state, the event extracting unit 141 regards it as a movementevent or determines it not as an event but as a numerical value such asspeed.

Then, the event extracting unit 141 adds an entry corresponding to theextracted event to the mobility event management table 133 and adds orchanges an entry corresponding to the target mobility instance to or inthe mobility instance state management table 134 (S902).

After the above process (S901 and S902) are performed for each mobilityinstance, the event aggregating unit 142 performs a process foridentifying the state of each infra capacity instance (steps S903 toS905).

Specifically, the event aggregating unit 142 performs the followingprocess (S903 to S905) for each infra capacity instance as a processtarget. In the description of FIG. 9, the infra capacity instance as aprocess target will be referred to as a target infra capacity instance.

The event aggregating unit 142 refers to the mobility instance statemanagement table 134 and identifies a series of mobility instancesbelonging to the target infra capacity instance within a specified rangeof time (S903). That a mobility instance belongs to a target infracapacity instance means that a geographical position of the mobilityinstance is near to the infra capacity instance. Whether a mobilityinstance belongs to a target infra capacity instance can be determinedby a map matching process or the like.

Next, the event aggregating unit 142 counts and totalizes the number ofparticular states (for example, speed reduction, stagnation and thelike) among the identified series of mobility instances, as thecongestion status of the target infra capacity instance (S904). Then,the event aggregating unit 142 adds the aggregated congestion status ofthe infra capacity to the infra capacity state management table 136(S905).

The event aggregating unit 142 performs the above process (S903 to S905)for each infra capacity instance as a target, and, after performing theprocess for all the infra capacity instances, ends the process.

Next, a process operation of the group data processing unit 116 of themanagement server 101 will be described.

FIG. 10 is a flowchart showing an example of a process by a group dataprocessing unit according to the embodiment.

The group data processing unit 116 performs the following process (S1001to S1004) to identify a group among the mobility instances 104.

First, the group possibility degree determining unit 151 performs aprocess (S1001 to S1003) for distinguishing weight information about agroup possibility degree for mobility data and giving the weight to themobility data.

Specifically, the group possibility degree determining unit 151 acquiresmobility data in a range between two specified time points, from themobility data management table 131 (S1001). Here, the two specified timepoints are time point to be a starting point of identifying mobilitydata to be used for a group identification process and time point to bean ending point. The ending point time point can be, for example,current time point. Further, the starting point time point may bearbitrary time point, for example, time point before a predeterminedtime from the current time point. The starting point time point can bechanged by the administrator of the management server 101.

The group possibility degree determining unit 151 performs the followingprocess (S1002 and S1003) for each piece of mobility data as a processtarget. In description of FIG. 10, the mobility data as a process targetwill be referred to as target mobility data.

The group possibility degree determining unit 151 performs a filteringprocess for target mobility data based on content of the filtering datamanagement table 161 and the filtering process management table 162(S1002). Specifically, the group possibility degree determining unit 151performs map matching for map data and lowers the degree of grouppossibility (weight) of target mobility data which is not on a generalroad (for example, which is on a railway track) (for example, sets thedegree to 0). Further, the group possibility degree determining unit 151lowers the degree of group possibility of such target mobility data thatdistances from the time point and position of mobility data of a publictransportation means are within predetermined ranges (for example, setsthe degree to 0).

Then, the group possibility degree determining unit 151 stores a resultof group possibility degree determination for the target mobility datainto the group possibility degree temporary management table 153(S1003).

After performing the above process (S1002 and S1003) for all the piecesof mobility data, the group extracting unit 152 performs the groupidentification process (see FIG. 11) for the pieces of mobility datawith group possibility degrees which have been stored into the grouppossibility degree temporary management table 153, allocates a uniquelyindependent group ID to each of extracted groups, and adds the group IDsto the mobility group management table 135 (S1004).

Next, the group identification process by the group extracting unit 152of the management server 101 will be described.

FIG. 11 is a flowchart showing an example of a group identificationprocess according to the embodiment. The group identification process isa process corresponding to step S1004 in FIG. 10.

The group extracting unit 152 acquires the pieces of mobility data withgroup possibility degrees which are temporarily stored, from the grouppossibility degree temporary management table 153 (S1101).

Then, the group extracting unit 152 decides a pair of mobility instancesto be a process target (the mobility instances are assumed to be A and Bin description of FIG. 11) among mobility instances corresponding to theacquired pieces of mobility data, and performs the following process(S1102 and S1103) for this pair.

First, for the pair of the mobility instances A and B, the groupextracting unit 152 calculates a same group degree D for determiningwhether or not the mobility instances A and B belong to the same groupwith regard to movement (S1102).

A method for calculation of the same group degree D by the groupextracting unit 152 will be described below. In the followingdescription, pieces of mobility data with group possibility degrees ofthe mobility instances A and B are expressed as multidimensional vectorarrays as below.A=((T_a1,X_a1,Y_a1,G_a1),(T_a2,X_a2,Y_a2,G_a2), . . . )B=((T_b1,X_b1,Y_b1,G_b1),(T_b2,X_b2,Y_b2,G_b2), . . . )

Here, (T, X, Y, G) corresponds to one entry of the group possibilitydegree temporary management table 153, and T, X, Y and G correspond to“time point”, “X coordinate position”, “Y coordinate position” and“group possibility degree” in an entry, respectively. Further, it isassumed that T_a1<T_a2< . . . and T_b1<T_b2< . . . are satisfied.

Paying attention to one entry (T_ai, X_ai, Y_ai, G_ai) of the mobilityinstance A, the group extracting unit 152 selects an entry (T_bj, X_bj,Y_bj, G_bj) of B having T_bj closest to T_ai, and calculates a samegroup degree D_i, which is one element of the same group degree D, bythe following formula (1). Though the entry of B having T_bj closest toT_ai is selected, the selection is not limited thereto. For example, anentry of B having T_bj close to T_ai (for example, within apredetermined range of time) may be selected.D_i=L(1−G_ai)+L(1−G_bj)+(α*(T_ai−T_bj)^2+β*((X_ai−X_bj)^2+(Y_ai−Y_bj)^2))  (1)

Here, α, β and L are parameters specified in advance.

The same group degree D_i is obtained by totalizing, for one piece ofmobility data of the mobility instance A, a value obtained by adjustinga value obtained by subtracting the group possibility degree of themobility data of A from 1, by L, a value obtained by adjusting a valueobtained by subtracting the group possibility degree of the mobilitydata of B from 1, by L, and a value obtained by adjusting time distanceand spatial distance by α and β. The same group degree D_i becomes asmaller value as the group possibility degree of the mobility data of Ais higher, as the group possibility degree of the mobility data of B ishigher and as the time distance and spatial distance between A and B aresmaller. That is, the same group degree D_i becomes a smaller value asthe possibility of the same group is higher.

The group extracting unit 152 performs the calculation of the same groupdegree D_i for all the pieces of mobility data of the mobility instanceA. A set of the same group degrees D_i calculated in this way becomesthe same group degree D.

Then, the group extracting unit 152 determines whether or not themobility instances A and B belong to the same group with regard tomovement, based on the calculated same group degree D (S1103).Specifically, if, for thresholds N and M specified in advance, thenumber of D_i satisfying D_i<N is M or more, the group extracting unit152 determines that the mobility instances A and B belong to the samemobility group. For example, the threshold N may be 1. When thethreshold N is set to 1, it is possible to, if the group possibilitydegree of the mobility data of A or the group possibility degree of themobility data of B is set to 0 (that is, if the mobility data of A or Bis to be removed), prevent the mobility data from contributing todetermination that A and B belong to the same mobility group. That is,the process can be performed on the assumption that the mobility datahas been removed.

After performing the above process (S1102 and S1103) for all mobilityinstance pairs among mobility instances corresponding to the acquiredpieces of mobility data, as process targets, the group extracting unit152 generates and allocates a unique group ID to each of extractedgroups, adds the group IDs to the mobility group management table 135(S1104) and ends the group identification process.

As described above, according to the group identification process,whether or not mobility instances belong to the same group is determinednot by only point information about mobility data at a certainparticular time point but by movement trajectory data (pieces ofmobility data at a plurality of measurement points in the past) which islinear information. Therefore, it is possible to determine whethermobility instances belong to the same group or not with a high accuracy.Further, since whether mobility instances belong to the same group ornot is determined with the use of weight (a group possibility degree)regarding easiness of identification of mobility context for mobilitydata, it is possible to exclude or reduce influence of mobility datafrom which identification of mobility context is not easy and improvethe accuracy of group determination.

Next, a process by the notification content processing unit 117 of themanagement server 101 will be described.

FIG. 12 is a flowchart showing an example of a process by thenotification content processing unit according to the embodiment.

Performing the following process (S1201 to S1205), the notificationcontent processing unit 117 performs notification such as for guidingmobility instances to an appropriate provider capacity, according to thecongestion status of an infra capacity.

The notification necessity/unnecessity determining unit 171 judges thatnotification is necessary if a congestion status is at a predeterminedlevel or above and continues for a predetermined time or more, based oncapacity state information (congestion information) in the infracapacity state management table 136 (S1201).

Then, the notification content determining unit 172 performs thefollowing process of steps S1202 to S1205 for each infra capacityinstance judged to require to be notified as a process target. Indescription of FIG. 12, the infra capacity instance as a process targetwill be referred to as a target infra capacity instance.

First, the notification content determining unit 172 refers to themobility instance state management table 134 to identify a group ofmobility instances belonging to an area covered by a target infracapacity instance, based on position information about the target infracapacity instance (S1202).

Then, the notification content determining unit 172 refers to themobility group management table 135 to identify a group of mobilityinstances belonging to the same group (a mobility group) with regard tomovement, among the group of mobility instances identified at step S1202(S1203).

Then, the notification content determining unit 172 performs thefollowing process (S1204 and S1205) for each mobility group as a processtarget.

Specifically, the notification content determining unit 172 refers tothe profile management table 163 to identify the tastes of the processtarget mobility group (S1204). As a method for identifying the tastes ofthe mobility group, there is, for example, a method of determining alogical product or a logical sum for profile information about eachmobility instance belonging to the mobility group, which is recorded inthe profile management table 163.

Next, the notification content determining unit 172 refers to theprovider capacity state management table 132 and determines informationabout such a provider capacity instance that taste type and positioninformation is close to that of the mobility group and that the capacityis sufficiently enough for the number of members of the group or more,as notification content (S1205).

If having performed the process (S1204 and S1205) for all the mobilitygroups identified at step S1203 as process targets, the notificationcontent determining unit 172 performs the process (S1202 to S1205) foranother infra capacity instance as a process target. Then, havingexecuted the process (steps S1202 to S1205) for all infra capacityinstances judged to require to be notified as process targets, thenotification content determining unit 172 ends the process.

The notification content decided by the notification content determiningunit 172 in this way is transmitted to terminals 102 a of mobilityinstances (users) belonging to a notification target mobility group, bythe data delivering unit 181.

Next, description will be made on the GUI (Graphical User Interface) ofthe terminals 102 a which have received the notification contenttransmitted by the data delivering unit 181.

FIG. 13 is a diagram showing an example of the GUI of the user terminalaccording to the embodiment.

When the notification content is transmitted by the data delivering unit181, each of the terminals 102 a of the plurality of users belonging tothe transmission target mobility group receives the notification contentand displays similar notification content 1302 on its screen 1301.

In the example of FIG. 13, the notification content is a coupon for aneating house meeting the tastes of the users belonging to the mobilitygroup. As a result, it is possible to effectively guide all the usersbelonging to the same mobility group to move to the eating house withthis coupon as an incentive.

The present invention is not limited to the above embodiment but can beappropriately modified and practiced within a range not departing fromthe spirit of the present invention.

For example, in the above embodiment, instance type information may beincluded in the data the management server 101 accepts from a mobilityinstance or a capacity instance or may not be included in the data. Forexample, if the instance type information is not included in the data tobe accepted, a table which manages meta data regarding correspondencerelationships between mobility instance IDs and pieces of instance typeinformation may be stored in the management server 101 in advance sothat the metadata of this table may be used to identify type informationcorresponding to a mobility instance ID in accepted data. As for acapacity instance also, a table may be stored similarly to the case of amobility instance so that type information may be identified by asimilar process. Further, position information about a capacity instancealso may not be included in the data accepted by the management server101. For example, as for a capacity instance which does not move such asa facility, it is thought that position information is often notincluded in the data. If position information is not included in thedata to be accepted, a table which manages metadata regardingcorrespondence relationships between capacity instance IDs and pieces ofposition information (pieces of position information expressed byaddresses are also possible) may be stored in the management server 101so that position information about a capacity instance may be identifiedbased on the metadata of this table.

Further, though, in the above embodiment, weight regarding easiness ofidentification of mobility context is given to mobility data of amobility instance, and mobility data is treated as having beensubstantially removed by setting the weight to 0, the present inventionis not limited thereto. For example, in order to remove such mobilitydata that easiness of identification of mobility context is low, thatis, identification of mobility context is difficult, from processtargets, a process for removing such mobility data that identificationof mobility context is difficult from mobility data acquired at stepS1001 may be performed instead of the process of steps S1002 and S1003in FIG. 10. By doing so, for example, a processing load in thesucceeding group identification process (S1004) of the group extractingunit 152 can be reduced.

Further, though, in the above embodiment, various pieces of data aremanaged in a configuration using an RDB (Relational DataBase), thepresent invention is not limited thereto. The various pieces of data maybe managed by a data management system with a high scalability such asan appropriate KVS (Key-Value Store) in consideration of consistency ofdata.

Further, though, in the above embodiment, each of the management server101 and the various tables is expressed by one block diagram, thepresent invention is not limited thereto. The management server 101 andthe various tables may be distributed in consideration of scalability.The management server 101 may embodied by a plurality of computershaving hardware and software, and each functional unit may be embodiedby a computer having hardware and software. For example, a plurality ofmanagement servers may be prepared so that management targets of themanagement servers are divided according to geographical areas, and loadbalance and routing is performed by the gateway 106. In this case,correspondence relationships among the management targets, pieces ofposition information and network addresses of the management servers canbe managed by the gateway 106.

Further, though, in the above embodiment, an example is shown in whicheach of the functional units of the management server 101 is configuredby a processor executing a program, the present invention is not limitedthereto. Apart or all of the functional units may be configured, forexample, by hardware such as an integrated circuit. Further, in theabove embodiment, the program configuring the functional units andinformation such as tables and files may be provided by a recordingmedium in which a program code and the like are recorded. In this case,the functional units can be realized by a processor of a computerreading and executing the program in the recording medium. As therecording medium for supplying the program code, for example, a flexibledisk, CD-ROM, DVD (Digital Versatile Disc)-ROM, hard disk, SSD (SolidState Drive), optical disk, magneto-optical disk, CD-R, magnetic tape,non-volatile memory card, IC (Integrated Circuit) card, SD (SecureDigital) memory card, ROM or the like can be used. Further, it is alsopossible to, by delivering the program configuring the functional unitsvia a network, store the program into a storage unit of a computer suchas a hard disk and a memory or a storage medium such as a CD-RW and aCD-R so that a processor provided in the computer may read and executethe program code stored in the storage unit or the storage medium.Further, a part or all of the functional units of the management server101 may be realized by virtual hardware (a virtual machine).

What is claimed is:
 1. A mobility data processing apparatus identifying,for one or more movable mobility instances existing in real space,mobility context which is information indicating a characteristic of amovement relationship with another mobility instance, the mobility dataprocessing apparatus comprising: a mobility data managing unitconfigured to store pieces of mobility data including space informationand time information about the plurality of mobility instances; aprocess executing unit configured to execute a predetermined process forimproving identification of the mobility context, for the pieces ofmobility data; and a mobility context identifying unit configured to,based on a time distance and a spatial distance between a piece ofmobility data of one mobility instance and a piece of mobility data ofanother mobility instance, identify mobility context of the one mobilityinstance after the process by the process executing unit.
 2. Themobility data processing apparatus according to claim 1, wherein themobility context is information showing whether or not a mobilityinstance belongs to a group performing the same movement as the othermobility instance.
 3. The mobility data processing apparatus accordingto claim 2, wherein the mobility context identifying unit is configuredto, based on a time distance and a spatial distance between one piece ofmobility data of the one mobility instance and a piece of mobility datawith a short time distance among pieces of mobility data of the othermobility instance, identify whether or not the one mobility instance andthe other mobility instance belong to the same group performing the samemovement.
 4. The mobility data processing apparatus according to claim3, wherein the mobility context identifying unit is configured to, foreach of a plurality of pieces of mobility data of the one mobilityinstance, determine a time distance and a spatial distance from thepiece of mobility data with a short time distance among the pieces ofmobility data of the other mobility instance and identify whether or notthe one mobility instance and the other mobility instance belong to thesame group performing the same movement based on the time distance andthe spatial distance.
 5. The mobility data processing apparatusaccording to claim 1, wherein the predetermined process for improvingidentification of the mobility context is a process for giving weightwith regard to easiness of identification of the mobility context to thepieces of mobility data; and the mobility context identifying unit isconfigured to, based on the time distance and the spatial distancebetween the piece of mobility data of the one mobility instance and thepiece of mobility data of the other mobility instance, and the weightwith regard to the easiness of identification of the mobility contextgiven to the pieces of mobility data, identify mobility context of theone mobility instance.
 6. The mobility data processing apparatusaccording to claim 5, wherein the process for giving the weight withregard to the easiness of identification of the mobility context to thepieces of mobility data is a process for giving weight indicating thatthe easiness of identification of the mobility context is low to a pieceof mobility data showing being positioned on a railway track based onmap data; and the process executing unit is configured to give theweight indicating that the easiness is low to the piece of mobility datashowing being positioned on the railway track from among the pieces ofmobility data.
 7. The mobility data processing apparatus according toclaim 5, wherein the process for giving the weight with regard to theeasiness of identification of the mobility context to the pieces ofmobility data is a process for giving the weight indicating that theeasiness of identification of the mobility context is low to a piece ofmobility data showing being on a public transportation system mobilityinstance; and the process executing unit is configured to give theweight indicating that the easiness is low to the piece of mobility datashowing being on the public transportation system mobility instance fromamong the pieces of mobility data.
 8. The mobility data processingapparatus according to claim 1, wherein the predetermined process forimproving identification of the mobility context is a process forremoving a predetermined piece of mobility data without the easiness ofidentification of the mobility context from among the pieces of mobilitydata; the process executing unit is configured to remove thepredetermined piece of mobility data from among the pieces of mobilitydata; and the mobility context identifying unit is configured to, basedon the pieces of mobility data from which the predetermined piece ofmobility data has been removed, measure the time distance and thespatial distance between the piece of mobility data of the one mobilityinstance and the piece of mobility data of the other mobility instanceto identify the mobility context of the one mobility instance.
 9. Themobility data processing apparatus according to claim 8, wherein theprocess for removing the predetermined piece of mobility data is aprocess for removing a piece of mobility data showing being positionedon a railway track based on map data; and the process executing unit isconfigured to remove the piece of mobility data showing being positionedon the railway track from among the pieces of mobility data.
 10. Themobility data processing apparatus according to claim 8, wherein theprocess for removing the predetermined piece of mobility data is aprocess for removing a piece of mobility data showing being on a publictransportation system mobility instance; and the process executing unitis configured to remove the piece of mobility data showing being on thepublic transportation system mobility instance from among the pieces ofmobility data.
 11. The mobility data processing apparatus according toclaim 1, further comprising: a group identifying unit configured toidentify one or more mobility instances belonging to a group performingthe same movement based on the mobility context; and a data deliveringunit configured to, by transmitting data including the same content toterminals of the mobility instances belonging to the group performingthe same movement, cause the terminals to display the same content. 12.The mobility data processing apparatus according to claim 11, furthercomprising: a capacity instance managing unit configured to manageinformation showing statuses of accommodation of the mobility instancesof one or more capacity instances capable of accommodating the mobilityinstances; and an excess detecting unit configured to detect excess ofcapacities of the capacity instances; wherein if it is detected that thecapacity of the capacity instances is exceeded, the data delivering unitis configured to transmit information about another capacity instancethe capacity of which is not exceeded, to the mobility instancesbelonging to a group performing the same movement which is accommodatedin the capacity instance.
 13. The mobility data processing apparatusaccording to claim 12, further comprising: an extraction unit configuredto compare a plurality of pieces of mobility data of the mobilityinstance to extract a state of the mobility instance; and an aggregationunit configured to aggregate the statuses of accommodation of themobility instances based on states of the mobility instances andregister a result of the aggregation with the capacity instance managingunit.
 14. A mobility data processing method by a mobility dataprocessing apparatus identifying, for one or more movable mobilityinstances existing in real space, mobility context which is informationindicating a characteristic of a movement relationship with anothermobility instance, the mobility data processing method comprising:storing pieces of mobility data including space information and timeinformation about the plurality of mobility instances; executing apredetermined process for improving identification of the mobilitycontext, for the pieces of mobility data; and based on a time distanceand a spatial distance between a piece of mobility data of one mobilityinstance and a piece of mobility data of another mobility instance,identifying mobility context of the one mobility instance after theprocess.
 15. A mobility data processing system provided with amanagement server capable of performing communication via a network anda mobile terminal; wherein the management server comprises: a mobilitydata managing unit configured to store pieces of mobility data includingspace information and time information about the plurality of mobilityinstances; a process executing unit configured to execute apredetermined process for improving identification of the mobilitycontext, for the pieces of mobility data; and a mobility contextidentifying unit configured to, based on a time distance and a spatialdistance between a piece of mobility data of one mobility instance and apiece of mobility data of another mobility instance, identify mobilitycontext of the one mobility instance after the process is performed bythe process executing unit.